世界首顆靜止軌道海洋水色衛(wèi)星應(yīng)用研究進(jìn)展

王泉斌,秦 平,趙曉晨

(1.國家海洋局第一海洋研究所,山東青島266061; 2.中國海洋大學(xué)信息科學(xué)與工程學(xué)院,山東青島266100;3.青島科技大學(xué)海洋科學(xué)與生物工程學(xué)院,山東青島266042)

世界首顆靜止軌道海洋水色衛(wèi)星應(yīng)用研究進(jìn)展

王泉斌1,秦 平2,趙曉晨3

(1.國家海洋局第一海洋研究所,山東青島266061; 2.中國海洋大學(xué)信息科學(xué)與工程學(xué)院,山東青島266100;3.青島科技大學(xué)海洋科學(xué)與生物工程學(xué)院,山東青島266042)

海洋環(huán)境參數(shù)和赤潮、綠潮等海洋災(zāi)害在一天之內(nèi)會有明顯的變化,需要高頻率的觀測才能滿足監(jiān)測的需求,極軌水色衛(wèi)星觀測頻率低,而靜止軌道水色衛(wèi)星在觀測頻率方面具有絕對優(yōu)勢。2010年韓國發(fā)射了世界上第一顆靜止軌道海洋水色衛(wèi)星GOCI(Geostationary Ocean Color Imager),使小時級時間分辨率的水色遙感成為現(xiàn)實,各國科學(xué)家圍繞該數(shù)據(jù)迅速開展了大量研究工作。本文首先介紹了GOCI遙感器的主要參數(shù)信息及其數(shù)據(jù)處理軟件,然后綜述了GOCI自問世至2016年的主要研究進(jìn)展,涉及衛(wèi)星數(shù)據(jù)處理、產(chǎn)品質(zhì)量評價、海洋環(huán)境探測、海洋災(zāi)害監(jiān)測、海洋動力過程探測、大氣探測等方面,以期對我國水色遙感特別是靜止軌道水色遙感應(yīng)用研究提供參考。

GOCI;靜止軌道;遙感應(yīng)用;水色遙感

2010-06韓國發(fā)射了世界上第一顆靜止軌道水色衛(wèi)星COMS(Communication Ocean and Meteorological Satellite),其上搭載了水色成像儀GOCI(Geostationary Ocean Color Imager),不同于傳統(tǒng)極軌衛(wèi)星1 d只能過境1景次,GOCI每天可獲取時間間隔為1 h的8景影像,使小時級時間分辨率水色遙感成為現(xiàn)實[1-7],使得海洋環(huán)境、海洋災(zāi)害的逐時變化監(jiān)測成為可能。圍繞靜止軌道衛(wèi)星水色遙感,各國科學(xué)家都表現(xiàn)出了濃厚的興趣,研究雖剛起步不久,但發(fā)展較快。我國科學(xué)家也在跟蹤GOCI應(yīng)用研究的步伐。

本文對GOCI問世幾年來的相關(guān)研究進(jìn)展進(jìn)行回顧和評述,內(nèi)容涉及衛(wèi)星數(shù)據(jù)處理、產(chǎn)品質(zhì)量評價、海洋環(huán)境探測、海洋災(zāi)害監(jiān)測、大氣探測等方面。其中衛(wèi)星數(shù)據(jù)處理的研究進(jìn)展主要集中在大氣校正算法研究;海洋生態(tài)環(huán)境探測的研究進(jìn)展主要集中在海洋葉綠素濃度、懸浮物濃度等生態(tài)環(huán)境參數(shù)反演方法與應(yīng)用方面;海洋災(zāi)害監(jiān)測的研究進(jìn)展主要集中在海冰、綠潮等黃、渤海常見的環(huán)境災(zāi)害方面。通過對GOCI相關(guān)研究現(xiàn)狀的分析,希望能對我國水色遙感特別是靜止軌道水色遙感應(yīng)用研究提供參考。

1 GOCI及其數(shù)據(jù)處理軟件

GOCI是世界上第一個靜止軌道海洋水色傳感器,搭載在COMS衛(wèi)星上于2010-06發(fā)射,傳感器設(shè)計壽命為7 a,觀測范圍為2 500 km×2 500 km,觀測中心經(jīng)緯度為(130°E,36°N),可覆蓋我國渤海、黃海和東海部分海域。GOCI的軌道相關(guān)參數(shù)如表1所示,根據(jù)海洋水色的觀測目的,GOCI共設(shè)置了8個波段,其中6個為可見光波段,2個為近紅外波段,波段寬度10～40 nm,波段設(shè)置及對應(yīng)的用途見表2。韓國海洋衛(wèi)星中心(KOSC)負(fù)責(zé)數(shù)據(jù)的發(fā)布。

(王 燕 編輯)

表1 GOCI相關(guān)參數(shù)及與SeaWiFS的對比Table 1 Comparison of the parameters between the GOCI and the SeaWiFS

表2 GOCI的波段設(shè)置Table 2 GOCI band settings

KOSC專門開發(fā)用于GOCI數(shù)據(jù)處理的系統(tǒng)軟件GDPS(GOCI Data Processing System)(圖1),該軟件包括數(shù)據(jù)瀏覽、數(shù)據(jù)處理、數(shù)據(jù)分析和數(shù)據(jù)輸出等模塊。其中,數(shù)據(jù)處理模塊包含了大氣校正算法和常用的水色遙感產(chǎn)品反演算法,輸入GOCI L1B數(shù)據(jù),可生成瑞利校正反射率(Rrc)、離水輻亮度(Lw)、歸一化離水輻亮度(n Lw)、遙感反射率(Rrs)、葉綠素濃度、可溶性黃色有機(jī)質(zhì)(CDOM)和懸浮物濃度(SPM)等L2級海洋分析數(shù)據(jù)產(chǎn)品。

圖1 GDPS軟件界面Fig.1 Interface of GDPS software

2 GOCI研究進(jìn)展

作為世界上第一顆靜止軌道水色傳感器,GOCI的發(fā)射升空引起了國內(nèi)外眾多海洋水色研究者的關(guān)注,目前已有大量基于GOCI數(shù)據(jù)開展的研究工作。作者對2011—2016年國內(nèi)外主要期刊上發(fā)表的與GOCI數(shù)據(jù)相關(guān)的研究論文進(jìn)行了統(tǒng)計和分析,結(jié)果如圖2所示。針對GOCI的研究內(nèi)容主要集中在GOCI數(shù)據(jù)處理、GOCI數(shù)據(jù)質(zhì)量評價、海洋生態(tài)環(huán)境探測、海洋災(zāi)害探測、海洋動力過程探測及大氣探測等方面,其中GOCI數(shù)據(jù)在海洋生態(tài)環(huán)境監(jiān)測方面的應(yīng)用最為廣泛。

圖2 GOCI相關(guān)研究統(tǒng)計Fig.2 Statistics of the researches related to the GOCI

2.1 GOCI數(shù)據(jù)處理方法

GOCI數(shù)據(jù)處理方法的研究主要集中在大氣校正方面[8-11],Ahn等[8]基于SeaWiFS的標(biāo)準(zhǔn)大氣校正算法,利用一個紅光和近紅外波段水體反射率的區(qū)域性經(jīng)驗關(guān)系,發(fā)展了GOCI數(shù)據(jù)的大氣校正算法,該算法集成到了GDPS 1.1版本中,利用該算法進(jìn)行大氣校正后,GOCI的離水輻亮度與實測數(shù)據(jù)的比值接近于1,證明了該算法的有效性。Wang等[9]提出了一種利用近紅外波段的GOCI渾濁水體大氣校正算法,利用該方法對GOCI數(shù)據(jù)進(jìn)行大氣校正后,與MODIS衛(wèi)星的觀測數(shù)據(jù)具有很好的一致性。Kim等[11]針對GOCI L1級數(shù)據(jù)存在輻射偏差的問題,發(fā)展了一種雜散光校正方法,輻射偏差降至≤5%。

2.2 GOCI數(shù)據(jù)產(chǎn)品質(zhì)量評價

數(shù)據(jù)質(zhì)量的優(yōu)劣勢是水色衛(wèi)星數(shù)據(jù)能否在海洋探測中發(fā)揮重要作用的關(guān)鍵[12-22]。Oh等[18-19]、Lee等[20]、Cho等[21]開展了GOCI在軌性能模擬、在軌光學(xué)性能評估和在軌性能變化分析等方面的研究。Moon等[14]利用船基觀測數(shù)據(jù)評估了GOCI遙感反射率、葉綠素濃度、黃色物質(zhì)和懸浮物等產(chǎn)品的精度,結(jié)果表明,GOCI可見光波段遙感反射率的平均相對偏差為18%～33%;葉綠素濃度產(chǎn)品與實測數(shù)據(jù)的相關(guān)性較低(＜0.41),平均相對偏差為35%;黃色物質(zhì)產(chǎn)品與實測數(shù)據(jù)沒有顯著的相關(guān)性;懸浮物產(chǎn)品與實測數(shù)據(jù)的相關(guān)性優(yōu)于0.73。Lamquin等[16]基于MODIS,MERIS和實測數(shù)據(jù)評估GOCI輻亮度產(chǎn)品,結(jié)果表明,GOCI與MODIS,MERIS和實測數(shù)據(jù)具有較好的一致性,但GOCI的大氣校正算法會將大量的渾濁水體掩膜掉,需要后續(xù)研究中進(jìn)一步改進(jìn)。Xiao等[22]基于2012—2013年的實測氣溶膠光學(xué)厚度(AOD)數(shù)據(jù)評估了VIIRS,GOCI和MODIS的氣溶膠產(chǎn)品,結(jié)果表明,與其他傳感器相比,GOCI的氣溶膠產(chǎn)品精度有待提高。

2.3 海洋生態(tài)環(huán)境探測

海洋生態(tài)環(huán)境參數(shù)的反演是水色衛(wèi)星的重要應(yīng)用之一,研究者利用GOCI數(shù)據(jù)在葉綠素濃度、懸浮物濃度、光合有效輻射等生態(tài)環(huán)境參數(shù)反演方面開展了大量的研究工作[23-39]?；贕OCI可逐時獲取影像的優(yōu)勢,Choi等[26,29]、Ryu等[25]和劉猛等[24]分析了近岸懸浮泥沙的日變化特征。Qiu等[30]提出一種針對GOCI數(shù)據(jù)的黃河口懸浮泥沙濃度反演算法,該算法的平均相對偏差為34.2%;He等[31]利用GOCI數(shù)據(jù)發(fā)展了杭州灣水體懸浮泥沙反演算法,并利用反演結(jié)果分析了杭州灣懸浮泥沙的日變化特征。Qiu等[35]針對GOCI數(shù)據(jù)提出了一種高渾濁水體的濁度反演算法,利用該算法反演了2014-12-30浙江近岸海域8個時刻濁度,發(fā)現(xiàn)濁度從近岸到遠(yuǎn)岸,從上午到下午逐漸降低。金惠淑等[36]利用波段比值法建立了基于GOCI遙感影像的葉綠素a質(zhì)量濃度反演模型,以此探討利用GOCI數(shù)據(jù)估算湖泊水體富營養(yǎng)化程度的可能性,研究結(jié)果表明GOCI遙感數(shù)據(jù)具有對湖泊富營養(yǎng)化程度進(jìn)行監(jiān)測的潛力。Kim等[37]首先按照SPM濃度將水體分為三類,然后評估了波段比、熒光基線高度等葉綠素反演算法對GOCI的適用性,發(fā)現(xiàn)GOCI葉綠素濃度反演結(jié)果的平均偏差約為35%。Hwang等[38]基于長時間序列的GOCI數(shù)據(jù)分析了漢江口海域的懸浮物濃度變化。Kim等[39]基于GOCI數(shù)據(jù)估算了光合有效輻射(PAR),并基于實測數(shù)據(jù)進(jìn)行了檢驗,同時與MODIS結(jié)果進(jìn)行了對比,結(jié)果表明GOCI一天可獲取8景數(shù)據(jù)的優(yōu)勢能有效評估PAR的日變化。

2.4 海洋災(zāi)害探測

在海洋災(zāi)害探測方面,國內(nèi)外研究者利用GOCI數(shù)據(jù)開展了赤潮、綠潮等災(zāi)害的探測研究[40-48]。Son等[40]發(fā)展了針對GOCI數(shù)據(jù)的綠潮探測指數(shù)IGAG,該指數(shù)利用了555,660和745 nm三個波段,與NDVI, EVI和KOSC等綠潮探測常用方法相比,IGAG指數(shù)能否增強(qiáng)低密度綠潮在圖像上的信號強(qiáng)度。Lou等[41]基于GOCI數(shù)據(jù),采用修正的赤潮指數(shù)RI,分析了東中國海赤潮的日變化,結(jié)果表明,赤潮在14:30時面積達(dá)到最大。Hong等[42]利用GOCI和MODIS數(shù)據(jù),對黃海入海高營養(yǎng)污水進(jìn)行了監(jiān)測。Young等[43]將衛(wèi)星數(shù)據(jù)與數(shù)值模擬結(jié)合,分析了黃海和東海海面漂浮綠潮的漂移路徑,發(fā)現(xiàn)漂浮綠潮的漂移由海流和風(fēng)控制。Gong等[44]利用GOCI數(shù)據(jù)提取了黃海和渤海海冰的漂移方向和速度。Bak等[45]基于GOCI數(shù)據(jù)發(fā)展了一種赤潮監(jiān)測算法,并與傳統(tǒng)的赤潮監(jiān)測算法進(jìn)行了對比,可有效避免誤檢情況。劉文宋等[46]發(fā)展了一種基于GOCI數(shù)據(jù)的海冰厚度監(jiān)測算法,并基于實測進(jìn)行了檢驗,RMS為6.82 cm。

2.5 海洋動力過程探測

利用GOCI的逐時數(shù)據(jù)可進(jìn)行海冰漂移速度、海表流場等的探測[49-57]。Lang等[49]利用GOCI逐時產(chǎn)品估算了渤海海冰的漂移速度,并分析了海冰漂移的影響因素及各因素的貢獻(xiàn)率。Lou等[50]基于GOCI數(shù)據(jù)的逐時特性,利用MCC法估算了東中國海的海表流場,通過分析發(fā)現(xiàn)流速的短時間變化主要是受潮汐的影響。海洋中的中尺度渦能夠引起海表層葉綠素濃度的變化,利用GOCI的葉綠素濃度產(chǎn)品可觀測海洋的中尺度渦等海洋動力過程。Park等[51]利用GOCI的葉綠素濃度產(chǎn)品探測到了日本海的中尺度渦;Lim等[52]利用GOCI觀測到了反氣旋暖渦引起葉綠素濃度升高現(xiàn)象。此外,Park等[53-54]還利用GOCI逐時數(shù)據(jù)發(fā)展了潮汐訂正模型。Hu等[55]基于GOCI數(shù)據(jù),利用MCC方法計算了杭州灣海域的表面流場,同時評估了杭州灣海域的懸浮泥沙的快速沉降和再懸浮過程。Warren等[56]也利用GOCI和MCC方法數(shù)據(jù)開展了海表流場的分析工作。吳頡等[57]基于GOCI的總懸浮體數(shù)據(jù)分析了長江口海域表層懸浮體鋒面的變化特征,并對其機(jī)制進(jìn)行了初步分析。

2.6 大氣探測

Lee等[58]利用GOCI數(shù)據(jù)生成了空間分辨率為500 m的海上氣溶膠光學(xué)厚度產(chǎn)品,與地面觀測數(shù)據(jù)的相關(guān)性為0.99。Park等[59]將GOCI逐時氣溶膠產(chǎn)品與模式模擬相結(jié)合,用于監(jiān)測PM運移事件的次數(shù),證明了GOCI氣溶膠產(chǎn)品在PM監(jiān)測中的應(yīng)用潛力。Choi等[60]利用GOCI數(shù)據(jù)反演了東亞地區(qū)陸地和海洋的氣溶膠光學(xué)厚度(AOD)、細(xì)模態(tài)比(FMF)、單次散射比(SSA)等氣溶膠光學(xué)性質(zhì)。Yuan等[61]基于GOCI數(shù)據(jù)發(fā)展了一種海霧探測算法,并分析了海霧的逐時變化特征。

3 結(jié) 語

GOCI問世6 a間,在數(shù)據(jù)處理方法、數(shù)據(jù)產(chǎn)品精度評價等方面已開展相關(guān)研究工作,GOCI數(shù)據(jù)在海洋生態(tài)環(huán)境監(jiān)測、海洋災(zāi)害監(jiān)測、海洋動力過程探測和大氣探測等方面,特別是逐時變化監(jiān)測方面顯示了其獨特優(yōu)勢。

與此同時,值得注意的是,我國科學(xué)家在上述相關(guān)領(lǐng)域的工作還比較少,作為水色遙感領(lǐng)域的新興方向,希望能引起我國科學(xué)家的充分重視,迎頭趕上。

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Advances in the Application Study of the First Geostationary Ocean Color Imager

WANG Quan-bin1,QIN Ping2,ZHAO Xiao-chen3
(1.The First Institute of Oceanography,SOA,Qingdao 266061,China; 2.College of Information Science&Engineering,Ocean University of China,Qingdao 266100,China; 3.College of Marine Science and Biological Engineering,Qingdao University of Science&Technology,Qingdao 266042,China)

Marine environmental parameters and marine disasters such as red tide and green tide can change obviously within a day.Therefore,high frequency observations are required to meet the monitoring needs. The polar orbiting ocean color satellites are relatively lower in observation frequency,whereas the geostationary orbiting ocean color satellites have an absolute advantage in the observation frequency.The first geostationary orbiting ocean color satellite in the world,i.e.the Geostationary Ocean Color Imager(GOCI) was launched by South Korea in 2010,which has made the ocean color monitoring realized an hour level time resolution.Scientists around the world have quickly carried out a large amount research work by using the GOCI data.In the present paper,the major parameters and the data processing software of the GOCI remote sensor are introduced,and then the main advances in the researches of GOCI from its advent to 2016,which involve satellite data processing,product quality evaluation,marine environment and disaster monitoring,marine dynamic process detection,atmospheric sounding,and so on,are reviewed in order to provide references for the application of ocean color remote sensing in China,especially for the application of the geostationary ocean color remote sensing.

GOCI;geostationary;remote sensing application;ocean color remote sensing

December 12,2016

P715.7

A

1002-3682(2017)02-0071-08

10.3969/j.issn.1002-3682.2017.02.009

2016-12-12

中央級公益性科研院所基本科研業(yè)務(wù)費專項資金資助項目——中韓海洋功能區(qū)選劃政策及技術(shù)方法比較研究(2015G19)

王泉斌(1980-),男,工程師,碩士,主要從事海洋環(huán)境與資源管理、中韓海洋領(lǐng)域合作等方面研究.E-mail:wangquanbin@fio. org.cn